Principal Applied Machine Learning ScientistQualifications PhD and 2 plus years of professional experience, a MS degree and 5 plus years of professional experience or equivalent professional experienceQualifications in a technical field such as Mathematics, Data Science, Applied Analytics, Operations Research, Computer Science, Applied Science or EngineeringExperience using databases (e.g., Teradata, Snowflake, s3)Experience with querying languages (e.g., SQL, SparkSQL)Demonstrated advanced programming skills with Python, Pyspark, or C++Expertise in deep neural network architectures (CNN, LSTM, Bi-GRUs), attention networks and dynamic memory networksDemonstrated knowledge of advanced data science toolsets (e.g., Tensorflow, Pytorch, Scikit-Learn, Airflow, Spark)Experience with cloud computing solutions such as AWS, GCP, or AzureExperience working in containerization ecosystems (Kubernetes or Docker)Experience in consumable endpoints development and deployment (Web Applications, REST APIs)Knowledge in model risk management strategies (model registry, concept/covariate drift monitoring, Hyperparameter tuning)Experience using advanced computing technologies when needed (e.g. GPUs)Followed software engineering practices and collaboration tools (e.g. Git, Bitbucket, GitHub)Experience building and deploying advanced AI solutions to solve complex business problemsResponsibilities As the Principal Applied Machine Learning Scientist, you will help transform business processes through data-driven technology products.Reporting to the Senior Manager of Applied Machine Learning, you will build scalable machine learning applications by developing and deploying machine learning and deep learning models that improve the effectiveness of our business operations, designing machine learning processes against requirements and automating work across the organization to improve our speed and efficiency.Lead the design and implementation of technical solutions by applying the latest research and AI methods.Work with business to understand the problem space, identify opportunities, and translate business problems into technical solutions using machine learning frameworks.Research the latest techniques and technologies in the space of ML/AI, Intelligent automation, NLP, and evaluate their potential for specific business use cases.Build machine learning pipelines from brainstorming, prototyping, development, and deployment.Apply techniques such as classification, clustering, regression, NLP, deep learning (CNN, RNN, GANs), time series forecasting, and Bayesian methods to build scalable solutions.Research and develop techniques in the field of Large Language Models (LLM) and Generative AI.Manipulate high-volume, high-dimensionality data from multiple sources, visualize patterns, anomalies, relationships, and trends, and perform feature engineering and selection.Create scalable, efficient, automated processes for large scale data analyses, model development, model validation, and deployment.Collaborate with business, engineering, Machine Learning operations/DevOps, and product teams to design and implement AI solutions.Compensation This position is salaried and will pay between $139,740.00 - $214,710.00 and will include an annual cash bonus of 15%. The range provided is a guideline and not a guarantee of compensation. Other factors involved in offer decisions include, and are not limited to a candidate’s experience, qualifications, geography, and internal equity.Benefits Medical, dental, vision, and life insurance coverage starts day one.Paid time off (PTO) days and 6 company holidays per year.6% 401(k) company contribution each pay period.Education assistance, including financial counseling, tuition reimbursement, and low-cost degree options.Employee discounts, parental leave, and more.#J-18808-Ljbffr